Andrew J. Blumberg

This paper introduces RefCM, a method that improves cell type annotation in scRNA-seq data using optimal transport and integer programming, achieving accurate cross-technology, cross-tissue, and cross-species mappings.

The paper develops statistical methods to assess molecular codes' sparsity and efficiency in characterizing cell types across C. elegans and cancer, showing homeodomain proteins and HLA genes do so more effectively than random controls.

CellStitch improves 3D cell segmentation in anisotropic images using optimal transport, outperforming existing methods on anisotropic datasets.

This paper identifies a universal pattern in single-cell sequencing data and proposes a method to denoise it by distinguishing biological signals from artifacts.